What Works on LinkedIn (And Why)

Most LinkedIn advice falls into one of two categories: tactical tricks that aim to game the system or vague encouragement to "post consistently and engage authentically." Neither helps you understand how the platform actually works — which is what you need to make good decisions about your own strategy.

This is my attempt to explain the mechanics and the principles behind LinkedIn distribution (as of early 2026), so you can build something authentic that works for your specific goals rather than following someone else's playbook.

First, a little bit of framing for this piece: LinkedIn is about quality of reach, not volume. Getting your work in front of 200 people who might actually collaborate with you, hire you, partner with you, or challenge your thinking is worth more than 20,000 random impressions. That is baked into LinkedIn's 360Brew recommendation system, which distributes content based on semantic relevance, not raw popularity. Understanding that changes how you think about everything from posting frequency to what "good engagement" looks like. (I also have a separate piece up on getting your profile in shape for 360Brew and a longer format explanation of how 360Brew actually works.)

How the Algorithm Evaluates Your Content

The algorithm isn't mysterious, even if it's complex. A few mechanics matter enough to understand.

One post per day, max. A second post within the same 24-hour window requires roughly 3x the engagement to achieve the same reach as the first. The algorithm wants to distribute content from many voices, not let power users dominate feeds. The sweet spot for most people is 3-5 posts per week. Consistency matters more than volume — five posts one week followed by silence the next performs worse than a steady two or three.

The first hour is a test. When you publish, LinkedIn shows your post to roughly 2-5% of your network as a test cohort. What happens in that window — comment velocity, dwell time, saves — determines whether the post reaches a wider audience or dies quietly. Responding to comments within the first 15 minutes has an outsized effect on distribution. This means you need to post when you can actually be present for the next 30-60 minutes, not schedule something and walk away.

Saves matter more than anything else. Analysis of millions of posts consistently finds that one save drives roughly 5x more reach than a like and about 2x more than a comment. Saves signal lasting utility — someone found your content valuable enough to return to later. The practical question before you publish anything: would someone come back to this next week? If the answer is no, the post may get polite reactions but it won't earn distribution.

Rich formats outperform text. Documents and carousels carry a 1.45x reach multiplier over baseline. Images sit at 1.18x. Text-only posts come in at 0.88x. Part of this is visual attention — a carousel holds someone's gaze for 15-20 seconds on average versus 8-10 seconds for a text post. Dwell time is a confirmed ranking factor, so formats that hold attention earn algorithmic advantage. This doesn't mean every post needs a carousel. It means that when you have substantive content worth presenting visually, presenting it that way performs better.

Comment quality, not comment count. A substantive comment of 25+ words carries roughly twice the weight of a like. When commenters start replying to each other — not just to you — that drives roughly 2.4x more reach, because it signals you created an actual conversation rather than a broadcast. Meanwhile, engagement pods (coordinated groups liking and commenting on each other's posts) are actively detected and downgraded. The algorithm is a language model. It can read your comments and measure whether they're substantive or formulaic.

Understanding these mechanics isn't about gaming the system. The algorithm is designed to find content that people genuinely find useful — the mechanics just tell you how it measures "useful."

Audience Quality Over Audience Size

Something that runs counter to how most people think about social media: a bigger follower count doesn't necessarily help you on LinkedIn. It can actually hurt you.

Post performance is evaluated relative to your network size. A post that earns 50 substantive reactions from a 2,000-person network may algorithmically outperform one that gets 200 reactions from a 50,000-person network, because the engagement rate is higher. The algorithm reads this as a stronger signal of content quality.

360Brew makes this dynamic even more pronounced. The system distributes content based on semantic relevance — matching your post's topic to people interested in that topic — regardless of whether they follow you. If the algorithm understands your expertise domain (through your profile alignment and posting consistency), it can push your content to exactly the right people even if your network is small. A government technology specialist with 3,000 carefully curated connections can reach the same senior federal audience as someone with 30,000 connections, because distribution is based on topical match, not network size.

The implication is uncomfortable for anyone who's been playing the connection-request game: aggressively connecting with random people dilutes your engagement rate without improving who actually sees your work. A bloated network full of people who don't care about your topics makes every post look worse to the algorithm, not better.

The metric that actually matters is whether the right people are seeing your work. Not how many people, but which ones. Are the federal CIOs, the diplomatic innovation leaders, the transformation practitioners in your field engaging with your content? That's the signal. Total impressions is vanity.

What "Good Content" Actually Means Here

LinkedIn is a professional platform built for people trying to do things in the real world — close deals, build partnerships, influence decisions, advance careers. That context shapes what performs.

Content that helps people do their jobs better earns saves. Frameworks they can apply to a problem they're facing this week. Step-by-step processes grounded in real situations. Templates they can adapt. Data with non-obvious implications they can use in a presentation. This is the content that people bookmark and come back to, and saves are the signal that drives distribution. If you're wondering what format to use or what to write about, start there: what do you know that would help someone in your professional community do their job better?

Professional and personal milestones also perform well, and for a different reason. A genuine career update, a reflection on completing a difficult project, a lesson from something that didn't work — these resonate because they're specific and authentic. They carry the weight of real experience, not generic advice. People engage with them because they recognize something true about their own professional lives.

What bombs is the opposite of both: content that's neither useful nor genuine. Single photos with a minimal caption. Vague motivational posts. Generic industry commentary that could have been written by anyone — what I think of as the horoscope test. If your post could apply to any professional in any industry, it's probably not specific enough to earn distribution. The algorithm reads your text semantically. It can tell when you haven't actually said anything.

There's a tension worth naming. 360Brew optimization — profile-content alignment, topic consistency, the mechanics I described above — is necessary for distribution. But it's not sufficient. People engage with people, not with optimized content machines. Your distinct perspective — the opinions not everyone would agree with, the specific details only you would know, the way you frame problems that comes from years of actually working on them — is what makes someone stop scrolling. You need both: algorithmic alignment so the system sends your content to the right people, and genuine human personality so those people actually care when they see it. One without the other doesn't work.

What Doesn't Work (And Why)

A few patterns reliably underperform, and understanding why helps you avoid them.

Company pages are nearly invisible. Personal profiles generate roughly 561% more reach than company pages sharing identical content. Company page organic posts now reach about 1.6% of followers — down from 7% a few years ago. If your organization's LinkedIn strategy depends on the company page, you effectively don't have a LinkedIn strategy. The platform is designed around people, not brands. Employee advocacy through personal profiles is the primary organic distribution mechanism, and every company that's figured out LinkedIn reach knows this.

Bland content provides no signal. A reshare with no added perspective. A photo tagged "Great event!" A post that's just a link. These give the algorithm nothing to work with — no semantic content to match, no substance to classify. If you wouldn't save it yourself, don't post it.

External links cost reach. Posts with links in the body see roughly 45% less reach — LinkedIn wants people to stay on the platform. Links in the first comment perform slightly better (about 15% less reach). Interestingly, posts bundling four or more links as curated resources actually see a boost, because the algorithm reads them as valuable reference material rather than promotional link drops. If you need to link out, first comment is the pragmatic choice.

Video is struggling. Median video reach dropped 72% year-over-year. Video still technically outperforms text-only posts (1.10x multiplier), but the investment-to-return ratio is poor. Short vertical video with captions remains the best-performing video format if you're going to use it — but for most people, the same time invested in a well-structured text post or document will produce better results.

Algorithm gaming gets detected. Engagement pods, hashtag stuffing, first-comment link tricks — these are artifacts of an older system that counted clicks. 360Brew is a language model. It reads your content, evaluates your engagement patterns, and measures lexical diversity in your comments. Coordinated, formulaic engagement looks different from organic engagement, and the system knows the difference.

Building From Principles

Now that you understand how the platform works, you can build a strategy from first principles rather than following someone else's template.

Start with your goal. What do you want LinkedIn to do for you? Attract clients? Build peer relationships in your field? Establish yourself as an expert in a specific domain? Get recruited? The answer shapes everything — what you post about, who you engage with, which metrics you should actually track.

Pick 2-3 core topics that align with that goal and your genuine expertise. Post 80% or more within those topics, especially in the first 90 days. That's the period where 360Brew is learning how to classify you — it needs consistent signals to understand what you're about and who should see your content.

Optimize for saves, not likes. Before posting, apply the test: would a professional in my community come back to this next week? If the answer is no, either make the content more substantive — add the specific framework, the concrete example, the template — or reconsider whether it's worth posting.

Be present in the golden hour. Post when you can spend 30-60 minutes engaging with the comments. That first hour determines whether your post reaches a wider audience. Responding quickly to comments isn't just polite — it has a measurable effect on distribution.

Engage with your target community. Your comment history trains the algorithm on which professional community you belong to. Five substantive comments on posts in your domain are worth more than fifty likes on random content. When you comment, add perspective — your experience, a different angle, a question that deepens the discussion. That's the engagement that signals expertise.

Track what matters. Saves per post. Substantive comments. Profile views from people in your target audience. Not total impressions, not follower count, not like totals. The vanity metrics feel good. The quality metrics tell you whether your strategy is working.

The Core Principle

LinkedIn rewards substance because it's built for professionals who are trying to accomplish real things — partnerships, deals, influence, career advancement. The algorithm is complicated, but the strategy that emerges from understanding it is straightforward: share genuine expertise on topics you actually know, in your own voice, consistently, and engage meaningfully with the professional community you want to be part of.

The platform is designed to help that work. The mechanics I've described above are just the system's way of finding content that actually helps people and distributing it to the people who need it. Align your profile, post within your expertise, create content worth saving, show up for the conversation. The algorithm handles the rest.